Trinity 大幅提昇企業面對大量快速變化資訊潮流時的競爭力。
現今企業 BI 多建於 RDBMS 上,伴隨大量的 ETL 與資料交換作業。在導入 Hadoop Big Data 應用之後, 如何有效地與既有 BI 系統介接,且進一步整合,以發揮整體綜效,將是一項挑戰。
Trinity 藉由優越的架構,在傳統 Structured Data 與 Hadoop Big Data 的應用間,建立無縫的交換作業,讓資訊分析人員直接運用熟悉的方式,以大幅降低導入 Big Data 應用時的學習曲線與後續對系統維運所投入的人力。
Trinity 大幅提昇企業面對大量快速變化資訊潮流時的競爭力。
現今企業 BI 多建於 RDBMS 上,伴隨大量的 ETL 與資料交換作業。在導入 Hadoop Big Data 應用之後, 如何有效地與既有 BI 系統介接,且進一步整合,以發揮整體綜效,將是一項挑戰。
Trinity 藉由優越的架構,在傳統 Structured Data 與 Hadoop Big Data 的應用間,建立無縫的交換作業,讓資訊分析人員直接運用熟悉的方式,以大幅降低導入 Big Data 應用時的學習曲線與後續對系統維運所投入的人力。
Can data virtualization uphold performance with complex queries? (Chinese)Denodo
Watch full webinar here: https://bit.ly/3fQFUEY
There are myths about data virtualization that are based on misconceptions and even falsehoods. These myths can confuse and worry people who - quite rightly - look at data virtualization as a critical technology for a modern, agile data architecture.
We've decided that we need to set the record straight, so we put together this webinar series. It's time to bust a few myths!
In the first webinar of the series, we’ll be busting the 'performance' myth. “What about performance?” is usually the first question that we get when talking to people about data virtualization. After all, the data virtualization layer sits between you and your data, so how does this affect the performance of your queries? Sometimes the myth is perpetuated by people with alternative solutions…the ‘Put all your data in our Cloud and everything will be fine. Data virtualization? Nah, you don’t need that! It can't handle big queries anyway,’ type of thing.
Register this webinar as we explore the basis of the 'performance' myth and examine whether there is any underlying truth to it.
How Enterprises Leverage Data to Overcome Business Challenges During CoronavirusDenodo
Watch full webinar here: https://bit.ly/2Jgb1uc
Coronavirus is spreading all over the world and has big impact on all the industries. How to acquire latest virus information from different countries and regions in real time to help organizations strategically plan and take actions accordingly and timely becomes very important.
Attend this webinar to learn:
- How business department acquires trustworthy data, gain deeper insights and fasten decision making
- How IT easily supports dynamic business requirements in real time
Can data virtualization uphold performance with complex queries? (Chinese)Denodo
Watch full webinar here: https://bit.ly/3fQFUEY
There are myths about data virtualization that are based on misconceptions and even falsehoods. These myths can confuse and worry people who - quite rightly - look at data virtualization as a critical technology for a modern, agile data architecture.
We've decided that we need to set the record straight, so we put together this webinar series. It's time to bust a few myths!
In the first webinar of the series, we’ll be busting the 'performance' myth. “What about performance?” is usually the first question that we get when talking to people about data virtualization. After all, the data virtualization layer sits between you and your data, so how does this affect the performance of your queries? Sometimes the myth is perpetuated by people with alternative solutions…the ‘Put all your data in our Cloud and everything will be fine. Data virtualization? Nah, you don’t need that! It can't handle big queries anyway,’ type of thing.
Register this webinar as we explore the basis of the 'performance' myth and examine whether there is any underlying truth to it.
How Enterprises Leverage Data to Overcome Business Challenges During CoronavirusDenodo
Watch full webinar here: https://bit.ly/2Jgb1uc
Coronavirus is spreading all over the world and has big impact on all the industries. How to acquire latest virus information from different countries and regions in real time to help organizations strategically plan and take actions accordingly and timely becomes very important.
Attend this webinar to learn:
- How business department acquires trustworthy data, gain deeper insights and fasten decision making
- How IT easily supports dynamic business requirements in real time
The art of storytelling and how it can help make a better world(mostly) TRUE THINGS
"Storytelling the most powerful way to put ideas into the world today," according to master storyteller Robert McKee. This power point is about why story matters in a world of constant change and so much information to absorb at ever-increasing speed, and the importance of learning the art of story for maximum impact on the listener. Presented at the Applied Improvisation Network annual conference in Montreal on Sept. 28, 015.
2012.05.24 於 「Big Data Taiwan 2012」的 Keynote 講稿。
主講者:Etu 副總經理/ 蔣居裕
《議題簡介》
無論是企業區域網路,還是開放的網際網路,在巨大的結構化與非結構化資料的背後,其實充滿著各種行為意圖,以及人、事、物、時、地的多維度關聯。商業的日益競爭,已經來到了一個除了講求行銷創意,還要擁有巨量資料處理與分析技術,才能出奇制勝的時代。有人形容 Big Data 的價值挖掘,就像是在攪拌混凝土,若在尚未完成前就中斷,將導致前功盡棄,全無可用的窘境。對 Big Data 的意圖與關聯探索,必須是 End-to-End 全程的照料,方得實現。本議程將舉例說明這個有序到永續的過程,讓聽者更能領略意圖與關聯充滿的世界。
1. “ 大 ” 、 “ 小 ” 是个相对概念 2. “ 大 ” 95% 以上都只是以指数级持续增长的数据,这是与增强的处理能力和存储容量相匹配的,或者至少是随之增长的。 3. http://www.computerworld.com/s/article/9087918/Size_matters_Yahoo_claims_2_petabyte_database_is_world_s_biggest_busiest?taxonomyId=53&intsrc=kc_feat&taxonomyName=databases Size matters: Yahoo claims 2-petabyte database is world's biggest, busiest Year-old database processes 24 billion events a day http://it.toolbox.com/blogs/oracle-guide/worlds-largest-database-runs-on-postgres-24979 According to an article at Computerworld , Yahoo is running a 2 PB (not GB, not TB, PB - Petabyte) database that processes 24 billion events a day. Let's put that in persp ective. 24 billion events is 24,000 million events; 24,000,000,000 events. 1 petabyte is 1,000,000,00 0,000 bytes. Yahoo has two of those. Actually, I should be basing this on 1k which is 1024 but when you're dealing with petabytes, I don't think we need to be picky. We're talking really, really big. Yahoo uses this database to analyze the browsing habits of its half a billion monthly visitors. How would you like to tune those queries? Do you think they allow ad-hoc access? 企业的数据可以分为 3 种类型:结构化数据、半结构化数据和非结构化数据。其中, 85% 的数据属于广泛存在于社交网络、物联网、电子商务等之中的非结构化数据。这些非结构化数据的产生往往伴随着社交网络、移动计算和传感器等新的渠道和技术的不断涌现和应用。企业用以分析的数据越全面,分析的结果就越接近于真实 美国奥巴马总统委员会的科学技术( PAST )顾问、 Teradata 公司首席技术官 Stephen Brobst 告诉《商业价值》记者:“过去 3 年里产生的数据量比以往 4 万年的数据量还要多,大数据时代的来临已经毋庸置疑。我们即将面临一场变革,新兴大数据将成为企业发展的当务之急,而常规技术已经难以应对 Pb 级的大规模数据量。这一变化所带来的挑战,是成功的企业在未来发展过程中必须要面对的。只有那些能够运用这些新数据型态的企业,方能打造可持续的重要竞争优势。” 沃尔玛是最早通过利用大数据而受益的企业之一,一度拥有世界上最大的数据仓库系统。通过对消费者的购物行为等非结构化数据进行分析,沃尔玛成为最了解顾客购物习惯的零售商,并创造了“啤酒与尿布”的经典商业案例。早在 2007 年,沃尔玛就建立了一个超大的数据中心,其存储能力高达 4Pb 以上。《经济学人》在 2010 年的一篇报道中指出,沃尔玛的数据量已经是美国国会图书馆的 167 倍。 现在, eBay 的分析平台每天处理的数据量高达 100PB ,超过了纳斯达克交易所每天的数据处理量。为了准确分析用户的购物行为, eBay 定义了超过 500 种类型的数据,对顾客的行为进行跟踪分析。 通过对广告投放的优化,自 2007 年以来, eBay 产品销售的广告费降低了 99% ,顶级卖家占总销售额的百分比却上升至 32% 。 沃尔玛、 eBay 等领先企业在大数据方面的获益,毫无疑问起到了示范作用。 IBM 不久前发布的“全球 CIO 调查之 CIO 重要启示”指出,已经有 83% 的 CIO 拥有涵盖商业智能和分析的远期计划,并且 CIO 们开始更多地关注数据,而非应用。 ITValue 社区的调研结果也显示, 57% 的中国 CIO 对数据的关注程度超过应用。 一方面,商业智能的普及,让企业对数据的重要性已经有了充分认识;另一方面,社交媒体、电子商务、物联网等新应用的兴起,打破了企业原有价值链的围墙,仅对原有价值链各个环节的数据进行分析,已经不能满足需求。他们需要借助大数据战略打破数据边界,了解更为全面的运营及运营环境的全景图 一方面,商业智能的普及,让企业对数据的重要性已经有了充分认识;另一方面,社交媒体、电子商务、物联网等新应用的兴起,打破了企业原有价值链的围墙,仅对原有价值链各个环节的数据进行分析,已经不能满足需求。他们需要借助大数据战略打破数据边界,了解更为全面的运营及运营环境的全景图 3 月 11 日日本大地震发生后仅 9 分钟,美国国家海洋和大气管理局( NOAA )就发布了详细的海啸预警。随即, NOAA 通过对海洋传感器获得的实时数据进行计算机模拟,制作的海啸影响模型出现在 YouTube 等网站。
我找不到我要的数据——数据分散在各个业务系统,各种版本,各种中间状态,各种不一致 比如电商:订单完成的状态以什么为准?退货怎么办? 业务员? BI 分析师? 我得不到我要的数据——数据集成,需要专家协助才能获得数据, DBA? 得到的数据不是我理解的数据——无文档,无元数据 我不能使用我找到的数据——结果不可信,数据还需要另外转化